Research Project 2
Develop an improved adaptative sampling method for Nanopore dRNA and cDNA sequencing
About the Project
University of Nottingham
Nottingham, UK
Oxford Nanopore Technologies
Oxford, UK
Matt Loose
Aino Järvelin
Supervisors
University of Nottingham
PhD enrolment
Yearly salary
20.162,01 €
Research Objectives
Little is known about transcriptome-wide epi-transcriptomic modifications and isoform diversity, especially of low abundance and biomedically relevant transcripts. Adaptive sampling (AS) is a strategy to enrich for specific transcripts in silico but its use in native RNA (dRNA) applications remains to be explored. Our objectives are:
- To test and further develop experimental and informatic tools for adaptive sampling on RNA.
- To demonstrate the utility of dRNA sequencing, enhanced by adaptive sampling, on analysis of RNA isoforms, tail lengths, and modifications.
- To apply these approaches to characterise transcriptome changes in a cancer cell line.
Envisioned Secondments
- Wobble (Kuo): Methods for cDNA normalisation and rare transcript annotation.
- CRG (Novoa): Epitranscriptomics data generation analysis.
- CSIC (Conesa): Learn statistics.
About the Supervisors and Host Groups
Aino Järvelin
Nanopore,
UK
I am interested in using genomics and data science to solve biological puzzles and to advance human and environmental health. I love to design new projects, distill complex datasets into actionable and insightful patterns, and translate between people from different disciplines and backgrounds whenever I can to create something new together. I actively promote help build open and inclusive work environments that enable people to learn, grow, and communicate. You’re sure to grab my attention with a nice data viz.
My core toolkit consists of R, python, and genomics tools and databases. With a background in experimental biology, have a strong understanding of how bio(medical) data is generated and the needs of wetlab experimentalists.
